# Data pipeline

The Fluent Bit data pipeline incorporates several specific concepts. Data processing flows through the pipeline following these concepts in order.

## Filters

[Filters](/manual/4.0/data-pipeline/filters.md) let you alter the collected data before delivering it to a destination. In production environments you need full control of the data you're collecting. Using filters lets you control data before processing.

## Buffer

The [`buffer`](/manual/4.0/concepts/buffering.md) phase in the pipeline aims to provide a unified and persistent mechanism to store your data, using the primary in-memory model or the file system-based mode.

## Inputs

Fluent Bit provides [input plugins](/manual/4.0/data-pipeline/inputs.md) to gather information from different sources. Some plugins collect data from log files, and others gather metrics information from the operating system. There are many plugins to suit different needs.

## Outputs

[Output plugins](/manual/4.0/data-pipeline/outputs.md) let you define destinations for your data. Common destinations are remote services, local file systems, or other standard interfaces.

## Parsers

[Parsers](/manual/4.0/data-pipeline/parsers.md) convert unstructured data to structured data. Use a parser to set a structure to the incoming data by using input plugins as data is collected.

## Route

[Routing](/manual/4.0/data-pipeline/router.md) is a core feature that lets you route your data through filters, and then to one or multiple destinations. The router relies on the concept of [tags](/manual/4.0/concepts/key-concepts.md#tag) and [matching](/manual/4.0/concepts/key-concepts.md#match) rules.


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# Agent Instructions: Querying This Documentation

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Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
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Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.